A Nine Variable Probabilistic Macroeconomic Forecasting Model

Christopher Sims ()

No 1034, Cowles Foundation Discussion Papers from Cowles Foundation, Yale University

Abstract: A model for U.S. macroeconomic time series that has been used for forecasting for several years is described in some detail. The model is a multivariate Bayesian autoregression, with allowance for conditional heteroskedasticity, stochastic time-variation in parameters, and non-normality of disturbances. It specifies the prior distribution in ways that improve on previous Bayesian vector autoregression specifications in realism and forecasting performance. The model's record of forecasting in recent years is displayed and discussed.

Date: Written
View list of references View citations in EconPapers

Downloads: (external link)
http://cowles.econ.yale.edu/P/cd/d10a/d1034.pdf (application/pdf)

Related works:
Chapter: A Nine-Variable Probabilistic Macroeconomic Forecasting Model (1993)
Working Paper: A nine variable probabilistic macroeconomic forecasting model (1989)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cwl:cwldpp:1034

Ordering information: This working paper can be ordered from
Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA
The price is None.

Access Statistics for this paper

More papers in Cowles Foundation Discussion Papers from Cowles Foundation, Yale University
Address: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Contact information at EDIRC.
Series data maintained by Glena Ames ().